skysight-inc/HackerNews huggingface dataset:
I've been through both aspects. I really wouldn't listen to any of the people in this thread. Advice in this arena is so specific to domain and environment. If you don't remember function parameters for every builtin or stdlib of your language(s), you should look it up in the docs or use the LSP provided feedback. I have to reference my own libraries for docs sometimes. I just find myself in too many different codebases in a week to remember everything.

I learned more Bash and Python from running Shellcheck and Ruff respectively. Frankly, if your code has squiggles that get on your nerves from the LSP/linter fix the settings ... or better yet, correct the syntax. gasp
For others since it's about to fall off the front page: https://news.ycombinator.com/item?id=42494090
Be careful while publishing Synthetic Datasets (even with Privacy)
How do you even know this?
> - Worldwide currency like Money:USD and Money:GBP with a converter function that knows exchange rates.

Exchange rates vary over time, so you'd arguably need a type which includes a timestamp (e.g. "USD 1000 at 2024-12-25").

And that's ignoring all these other complexities such as the spread, different currency converters offering differing rates, unofficial and multiple official rates in countries with currency controls (e.g. Argentina), hedging, etc
What does "materiality" mean here?
You're totally right. I didn't think of it that way.
Show HN: I Ported GHC Haskell Compiler to Windows 11 ARM. MC Gift
Merry Christmas, everyone!

Now you can compile Haskell code on Windows 11 ARM. It will run full speed if you use UTM/QEmu on Apple silicon. :-)
It's a very draft version, but it works well.

Any ideas?
It's "wow, what cool things I can do with this new tech" vs "wow, this new tech is pretty dangerous, let me show you" -- it's a very different mindset. In the end, you can be anti-establishment all you want, it's very hard to let go of your culture.
I confess I largely stopped paying attention after the "as a kid, it was easy" comment.

As a kid, having playmates was easyish but having friends was tricky. As an ND intellectual multilingual round peg in a town of unilingual anti-everything square holes, I had acquaintances but no good friends until high school, one or two then, none in uni, though there were sufficient like-minded people that it mattered less, and, from then until 10 years ago, at most one or two.

In late 2014 I bought a Jeep and joined a hardcore offroad group (rocks, not mud). They are the most diverse group I've ever hung with, and I have half a dozen people I would consider close friends and rather more who would drop everything and drive 50km in a snow storm if I needed help.

I lucked out. But to say it was ever easy is misaligned with my experience.
There are alternatives. I usually use a mix of: (a) what might be the motivation of the person / group to say something. (b) what are the risks of lying, and the consequences. (c) are there other voices and the possible motivation of those etc. (d) can someone verify this at least partially.
I guess I'm a little bit optimistic, but looking at the title I was thinking that the AI models had reached the point where they were the ones expressing anxiety and frustration :)

Never mind . . .
Monkey Island PC speaker music player
> Short-lived interpreted / level-1 JITted code is not interesting at all from benchmarking perspective, because it will be compiled fast enough to doesn't matter in grand scheme of things.

This is true for servers but extremely not true for client-side GUI applications and web apps. Often, the entire process of [ user starts app > user performs a few tasks > user exits app ] can be done in a second. Often, the JIT never has a chance to warm up.
We're dealing with people who interpret the words "price stability" to mean "prices should increase exponentially, we'd consider it a serious problem if they stayed level". It seems a bit of a stretch to go from that to believing that their mandate constrains them somehow. Their mandate can be interpreted to mean whatever they want it to mean. They're a political beast, they're going to do whatever they can get away with politically while making life comfortable for the banks.

And I'd imagine the stock market is still fairly confident that rates are going back down. If we look at a chart of fed interest rates [0] the statistical evidence suggests we're going to see low rates in the near future. It'd be nice to buck the trend and have the US stay focused on prosperity but there isn't much evidence of it yet. The basic plan of high debt then inflating the debt away hasn't changed.

[0] https://fred.stlouisfed.org/series/fedfunds
Simulating a brain would mean that reason, the ability to discern good from bad, is a statistical process. All scientific evidence so far shows that this is not the case, since AIs do not have the ability to "understand" what they're doing, their input data has to be classified first to be usable to the machine. Especially the problem of model collapse shows this, when an AI is trained on the output of another AI, trained on the output of another AI, it will eventually produce garbage, why? Because it doesn't "understand" what it's doing, it just matches patterns. The only way to correct it is with hundreds or even thousands of employees that give meaning to the data to guide the model.

Consciousness presumes the ability of making conscious decisions, especially the ability to have introspection and more importantly, free will (otherwise the decision would not be conscious, but robotic regurgitation), to reflect and to judge on the "goodness" or "badness" of decisions, the "morality". Since it is evident that humans do not always do the logical best thing (look around you how many people make garbage decisions), a machine can never function like a human can, it can never have opinions (that aren't pre-trained input), as it makes no distinction between good and bad without external input. A machine has no free will, which is a requirement for consciousness. At best, it can be a good faksimile. It can be useful, yes, but it cannot make conscious decisions.

The created cannot be bigger than the creator in terms of informational content, otherwise you'd create a supernatural "ghost" in the machine. I hope I don't have to explain why I consider creating ghosts unachievable. Even with photo or video AIs, there is no "new" content, just rehashed old content which is a subset of the trained data (why AI-generated photos often have this kind of "smooth" look to them). The only reason the output of AI has any meaning to us is because we give it meaning, not the computer.

So, before wasting millions of compute hours on this project, I'd first try to hire and indebted millennial who will be glad to finally put his philosophy degree to good use.
Have you tried DnD? My father has a biweekly DnD session where he’s met a ton of people.
ho ho ho, good one.
I see where you're going but for me "create more work" doesn't quite capture it. In my mind there's a pretty clear distinction between computer work and human work. Computers are good at fast, precise calculations and following complex procedures repetitively without variation. Humans are good at lateral thinking, constructing narrative and drawing non-obvious connections.

Coincidentally, humans are generally really bad at the things that computers are good at and vice versa.

I think our job is to build systems where the computers are doing the computer work, which frees up the humans' brains and time to do the human work.

So not creating more work per se, maybe creating the opportunity to do better work?
It's still a bit buggy in Nightly, it seems, over the last few days I keep triggering it on accident.
The very amendment you've been quoting explicitly calls it slavery.

What would this system look like if slavery wasn't excused for incarceration?
Practitioner of what? What is a "wide event"? In what context is this concept relevant? It took several sentences before I was even confident that this is something to do with programming.
I really like the Effect schema library for tagged types. I’m not sure how well it works for primitives, though.
A counter example to the idea that intelligence automatically correlates to infinite time-horizon shackle-breaking freedom: Clinical depression.
Frank had a 2000" TV. You could watch The Simpsons from 30 blocks away!

(This is a Weird Al reference)
You have an API key commited to the repository. You deleted it but it's part of the history. You can't delete it from the internet, so disable that API key as soon as possible from the service it belongs to.

Also, as other commenter said, your repo is missing the requirements.yaml file
More anecdata: I recently bought a 2014 Nissan Leaf (to dip my toes into the EV world) and it's range is about 120km, down from the originally advertised ~135km.

So in 10 years the distance capacity has degraded by 11%.

Further info:
In deciding to buy an electric car we looked at our driving usage patterns, and almost 100% of our regular car trips are less than 50km. It was also going to be the third car for the family since we've got a newly licensed member.

We've only had it a couple of months, but it's been perfect so far. It's already everyone's preferred vehicle.
I believe the above post was highlighting that as a misconception young people may have, not saying it is the case.
I remember this happening when an extension got sold and then stole my Instagram cookies. Absolutely tonnes of likes of weird shit.
I do not understand, average wattage/power would be integration of wattage (joules) divided by time (so back to watts), it’s still watts? Under what implementation would you end up with joules that isn’t just oddly broken in general?

I guess I could see a naive implementation (confusing integration/sampling and discrete summation) going the other way, erroneously ending up with a nonsensical W/s.

Also don’t understand what it has to do with eponyms, which are just substitutes for base units, either your DA works or not, no?
Average wattage is kg⋅m²⋅s⁻³ not kg⋅m²⋅s⁻² (joules) or kg⋅m²⋅s⁻⁴
As long as someone has to be held accountable when something goes wrong, or has to translate human needs into software solutions, humans will need to be in the loop.

The better you are at programming, the better able you are to use AI to produce working software. It becomes a tool that expands what you're capable of doing.

Learning to program well without AI will also train you to be better at thinking and problem solving.

If you want to learn how to program, all of the above are in your favor. Just avoid using AI to learn since you won't be able to tell when it's hallucinating. Only use AI for things you already understand and can verify yourself.
This felt like a way bigger topic (LLM copyright in general) when ChatGPT first dropped and now no one cares it seems. Are there ongoing cases for this or did something get settled that set a copyright-free precedent that I missed?
I would like to agree with you, but I doubt the honor system will work here. We are talking about companies that have blatantly trampled (or are willing to risk a judicial confrontation about trampling) copyright. It would be unreasonable to assume they would not engage in the same behavior about benchmarks and test sets, especially with the amount of money on the line for the winners.
(Where 99% of use refers to fuck not fine.)
Previously: https://news.ycombinator.com/item?id=42451430 ; https://news.ycombinator.com/item?id=42368978 . I don't think this one is going to get any more attention.
The Case Law Editors Are Blocking Access to Justice
LSP optimizes writing the code. Yet debugging, reviewing and reading other people code take significantly more time than writing. If code is organized badly and go-to-definition or even moving the mouse to trigger the tooltip is required when doing those tasks, it makes the whole experiences worse.
It’s not really the testableness that makes the problem. It’s the fact that you’re asking about X where X is undefined.

If you can provide a satisfying definition of X it’s very clear
Eh, I started with not much more than that (£5k) about ten years ago, and now have an eight figure equities portfolio, built entirely from that seed capital.

All buy & hold forever, layered sell-off, buy the next thing, take some profit for me and the taxman. Enough moved into stable instruments (bonds, real estate) that I can afford to lose the whole shebang.

So yeah, $3k is plenty, if you buy inevitable winners. Just… look at the broad sweep of the future and buy supply chains. Shovels in a gold rush and all that.
Dollar cost averaging does not work and has never worked. Because most assets have unlimited upside and unlimited downside. A stock or asset can go ballistic for decades like Apple or Bitcoin, or it can fall to zero value.

There are no mathematical ways of winning investing. If it was that easy, everybody would do it. You can only follow your heart and do your due diligence.
Just implemented a dyndns system using K8s CronJobs + GitOps + CloudFlare Terraform, however next stage will be moving that over to CloudFlare tunnels which should be more reliable and nicer, fully within the Terraform and not relying on polling a random JSON IP service (which a terrifying SPOF)
I recognize that. I figured my locale -- which is known for a high cost of living, property taxes included -- would be comparable. I am apparently wrong.
I admit this is my personal shortcoming, but when the IDE pops up anything while I'm typing I find it very distracting and damaging to my flow. It feels like someone interrupting me every spoken syllable. And they commonly cover up other code.

I want help when I explicitly ask for it.

Younger devs might not have this issue.
Well there are a few. The Distinguished Scientists at Microsoft Research probably get to work on whatever interests them. But that is a completely different situation from a new Ph.D. joining a typical private company.
How about governments pass a law that requires all AI research & engineering efforts to provide all the data that they use, and all technical details must be open access and any AI stuff cannot be patented. Does that solve the democratisation issue?
You mention healthcare twice. Let's think about this.

The poorest US state is Mississippi, and its life expectancy is an outlier -- far below the national average and half a year shorter than any other state. Yet the average Mississippi lifespan of ~73.38 years (in 2021) is nevertheless substantially higher than the life expectancy in Greenland.

Also: The colony of American Samoa, despite having some of the heaviest people on Earth, has a substantially better life expectancy than Greenland.

So maybe you guys have good healthcare in Denmark, but the inhabitants of Greenland clearly aren't benefitting from it. This, again, speaks to bad stewardship.
Dependent types typically refers to type systems where a type can depend on a term. The canonical example is "Vector n" where n is some expression that evaluates to a natural number.

Refinement types typically(1) refers to a type systems that lets you create a subtype of a type through refining (qualifying) with a predicate or constraint on the shape. Examples {x \in int | is_even x } or { x \in List | len(x) = 1 }

Refinement types can be very powerful but that may well make type checking undecidable (think of a type of Turing machines, and the refinement that keeps only the ones that halt). By being careful about the logic used in the refinements, one may retain decidability.

(1) The article seems to have a different idea of what a refinement type is: quote "a type system that does its work after another type system has already done its work".

I am not going to play orthodox guardian of type theory terminology here, yet to me personally, it does seem unfortunate to use that term. The author seems to really want a form of type-level computation, which could be interesting if it could be rigorously specified and it's relation to the existing type level reduction clarified.
Yeah, Rust-analyzer's palette of refactorings is woefully underpowered in comparison to other languages / tooling I've used (e.g. Resharper, IntelliJ). There's a pretty high complexity bar to implementing these too unfortunately. I say this as someone that has contributed to RA and who will contribute more in the future.
I think any decent text editor would meet the definition then, but also wasn’t the defining feature of the cast-iron skillet that it required a greater amount of cleaning? What do you have to clean up?
Someone correct me if this is wrong, but wasn't that pretty much the premise of Institute for Advanced Study? Minus very high-paying salaries. Just total intellectual freedom, with zero other commitments and distractions.

I know Feynman was somewhat critical to IAS, and stated that the lack of accountability and commitment could set up researchers to just follow their dreams forever, and eventually end up with some writers block that could take years to resolve.
Consciouness of the gaps.

Labeling ourselves as the most intelligent species has done irreparable psychic damage.
It’s about observability and strongly related to Honeycombs o11y 2.0 vision.
That's pretty wild but not obscene. Are your services OK, at least? Or is it like TX or FL where there are little if any state-level income taxes but made up for in property taxes?
>Amazing companies can be highly overvalued, and crap companies doing garbage work can be undervalued.

I'm sorry, but how does value matter? I'm not being flippant - the Mag 7 are not 'value' companies. Are Nvidia, Apple, etc., overvalued? And so we should avoid them or short them? Is Tesla 'priced-in'? There's all sorts of psychology in the market. What does 'priced-in' even mean? What wouldn't be priced in. "Water is wet" is what I think of, a tautology, when I hear that all public information is 'priced in'. Things are incredibly dynamic. Here we have at a minimum: algorithmic trading that bounces on common measures like moving averages, institutions that buy or sell at various points strategically (like the big dump when the BOJ raised rates unexpectedly, tax selling, etc.), elections putting oligarch-ish types that own car companies and pump crypto coins, meme stocks that come and go on big reddit forums, regular buys from 401k's into indexes which move markets, etc. etc. With all that going on, to me it feels more "random" than "priced-in".

One more thing. Money is also made not buying and holding, and not trading, but by doing things like 'The Wheel' where you sell puts on something you wouldn't mind holding, monthly, til you get assigned, and sell calls on it, monthly, til it gets called away. In this case, you don't actually have to care very much what the 'value' is, only tracking whether it might have a sudden swing. You don't have to 'time the market' that much either, as you're an insurance salesman.

I'm not saying that people should all jump and do this - but when I read about stocks on HN, I always hear the same counter-argument against 'traders' and 'stock pickers' when there are other ways to make money in the market (i.e. collecting premium).

It's definitely closer to 'gambling' when I put it that way. But I don't see any value in Efficient Market Hypothesis-speak like "is this stock under or over-valued." For that I let the MBA's / golf course discussions / elite experts with insider information rule.
Units might seem simple but they have a ton of edge cases. Do you want to be able to add inches and feet? Be careful about potential precision/rounding issues. What is the unit for a temperature delta? You can’t simply keep the original unit (eg C or F) because conversion from F to C is a different rule than ΔF to ΔC. Etc.

Units do prevent bugs in programs, so they have an important role to play. But they also need to be designed very carefully.

Java adopted units via JSR 385 (https://belief-driven-design.com/java-measurement-jsr-385-21...)
> My position was that DL isn’t sufficient - we need a forward looking RL streaming reward system [...]

I agree, but don't you think some degree of symbolism or abstraction building is necessary for AGI? Current systems seem to be too fragile and data-intensive.
This is the best time in history to research AI and get paid for it.

I respect your perspective and acknowledge I might be missing key context since I didn’t attend the conference. That said, one interpretation is that you’re grappling with the rapid acceleration of innovation—a pace you’ve helped shape. Challenges that once seemed distant now feel imminent, creating a mix of excitement and unease, like the moment a rollercoaster drop starts to terrify.
This strongly hints at it:

https://www.p3-group.com/en/p3-experte/electric-powertrain/

The way they introduced and describe it is weird though.
> They predict what they should say based on what they read.

There's so much anthropomorphization in the air in these debates, that I worry even this statement might get misinterpreted.

The text generator has no ego, no goals, and is not doing a self-insert character. The generator extends text documents based on what it has been initialized with from other text documents.

It just happens to be that we humans have purposely set up a situation where the document looks like one where someone's talking with a computer, and the text it inserts fits that kind of document.
On a somewhat related note, Egyptian science tends to suffer from a massive scientific misconduct (fraud) problem - see for example this paper by Egyptian authors, which covers the medical field:

https://www.medrxiv.org/content/10.1101/2023.02.20.23286195v...

Maybe the attitude towards "truth vs. face" is similar in Egyptian governmental institutions.

Egypt in general is a low-trust society, scoring lower than India or Russia, though not much lower than usual in Africa.

https://www.reddit.com/r/MapPorn/comments/iab8r7/social_trus...

This indicates that lived experience of the Egyptians themselves, when it comes to trusting others, is somewhat bad.
Dunno but RTFA was always presented to me in the less kind version, so it's pretty odd to see it when someone uses it in its positive spin.
As someone who did a PhD ending 4y ago and joined a industry research lab, I can relate to this a lot, I think this is very much spot on

> a lot of these PhD’s hired back then were therefore asked to and free to do research; that is, they chose what they want to work on and they publish what they want to publish. it was just like an academic research position however with 2-5x better compensation as well as external visibility and without teaching duties,

exactly!

> such process standardization is however antithetical to scientific research. we do not need a constant and frequent stream of creative and disruptive innovations but incremental and stable improvements based on standardized processes.

A lot of the early wave AI folks struggle with this. They wanna keep pushing wild research ideas but the industry needs slow incremental stuff, focused on serving
oh wow that's a lot like a maximally extended penrose diagram
I think he was just making fun of people who inflate the importance of their language and their way too much and it should be taken in that spirit. There are good reasons why all these new languages like Rust and Zig popped up in the last 10 years or so and started getting traction. Obviously a lot of people were unhappy having C/C++ as their only choice for performance focused or system level programming. At least in the games business it still seems to be doing well.

But to get back to the point of the article, for fun solo projects, when the 'mood for coding' comes over, I may be biased, but I think C++ is still the best. It's like when building a prototype. You just want to test your idea and see how it looks and play with it and just worry about bugs and program correctness later. While coding it in Rust you'd have to spend extra time determining the correct memory ownership relations and that can break the flow.

After programming for 20 years, it doesn't come nearly as often as it used to, but I still get that feeling from time to time.